Global Future Council on Data Frontiers

The rapid advancement of AI and genAI, along with the melding of human and machine capabilities, requires new frameworks for responsible data and IP governance.

AI-generated and synthetic data emerge as double-edged, offering significant opportunities to drive AI advancement, address data scarcity and strengthen privacy, but also complicating IP ownership while introducing risks such as amplification of biases, generation of misleading data and the specter of AI autophagy and “model collapse.”

How can the transformative potential of synthetic data and genAI be harnessed to preserve agency and ensure equitable outcomes, appropriate attribution, privacy safeguards and fair benefit sharing?

Members

Founder and CEO, Global Center on AI Governance

Rachel Adams

Principal Architect, Responsible Artificial Intelligence (AI) and Technology, Salesforce

Kathy Baxter

Chief Artificial Intelligence (AI) Officer, HealthAI, The Global Agency for Responsible AI in Health

Alberto Giovanni Busetto

Member of the Board, The Oversight Board

Nighat Dad

Head and Vice President of Meta India, Meta

Sandhya Devanathan

General Counsel and Head, Artificial Intelligence (AI) Governance, MILA - Quebec Artificial Intelligence Institute

Justine Gauthier

Vice-President, Research, Cohere

Sara Hooker

Associate Professor and Director, Te Kotahi Research Institute, University of Waikato

Maui Hudson

Chief Data Scientist, Cognizant

Kathrin Kind

Co-Founder and Chief Executive Officer, Twelve Labs

Jae Lee

Chair of Data Science; Associate Professor of Computer Science, University of Pretoria

Vukosi Marivate

President, National Institute of Statistics, Geography and Informatics (INEGI)

Graciela Márquez Colín

Executive Director, Ushahidi

Angela Oduor Lungati

Global Field Chief Technology Officer, Snowflake

Fawad Qureshi

IBM Fellow; Global Leader, Artificial Intelligence Ethics, IBM

Francesca Rossi

Managing Director, Centre for the Fourth Industrial Revolution, Rwanda

Crystal Rugege

Harold Price Professor, Entrepreneurship and Technology, Stern School of Business, New York University

Arun Sundararajan

Chief Executive Officer, Creative Commons

Anna Tumadóttir

Chief Executive Officer, DataKind

Lauren Woodman

Professor, Institute of Data Rule of Law, China University of Political Science and Law (CUPL)

Zhang Linghan

関連レポート

Advancing Data Equity: An Action-Oriented Framework

Automated decision-making systems based on algorithms and data are increasingly common today, with profound implications for individuals, communities and society. More than ever before, d...

報告書 — 2024年9月11日

Data Equity: Foundational Concepts for Generative AI

This briefing paper focuses on data equity within foundation models, both in terms of the impact of Generative AI (genAI) on society and on the further development of genAI tools.

報告書 — 2023年10月17日

Pathways to Digital Justice

The World Economic Forum’s Global Future Council on Data Policy liaised with the Global Future Council on Media, Entertainment and Sport and the Global Future Council on AI for Humanity t...

報告書 — 2021年9月29日

もっと読む関連するすべてのコンテンツ

Un marco para avanzar en la equidad de datos en un mundo digital

La equidad de datos es una responsabilidad compartida que requiere una acción colectiva para crear prácticas y sistemas de datos que conduzcan a resultados justos y equitativos para todos.

A framework for advancing data equity in a digital world

Data equity is a shared responsibility that requires collective action to create data practices and systems that promote fair and just outcomes for all.

How equitable data practices can shape the future of urban planning

Digital technologies have become ubiquitous in today’s urban environments. Facial recognition systems are used at sports and entertainment venues and public events. Vehicle mounted, camer...